Abstract Background: Natural Language Processing (NLP) is widely used to extract clinical
insights from Electronic Health Records (EHRs). However, the lack of annotated data …

Background Machine learning systems are part of the field of artificial intelligence that
automatically learn models from data to make better decisions. Natural language processing …

Suicide is a leading cause of death that defies prediction and challenges prevention efforts
worldwide. Artificial intelligence (AI) and machine learning (ML) have emerged as a means …

Suicide is a leading cause of death. A substantial proportion of the people who die by
suicide come into contact with the health care system in the year before their death. This …

In ever more pressured health-care systems, technological solutions offering scalability of
care and better resource targeting are appealing. Research on machine learning as a …

As avid users of technology, adolescents are a key demographic to engage when designing
and developing technology applications for health. There are multiple opportunities for …

(1) Introduction: Around a million people are reported to die by suicide every year, and due
to the stigma associated with the nature of the death, this figure is usually assumed to be an …

Objective Accurate and rapid phenotyping is a prerequisite to leveraging electronic health
records for biomedical research. While early phenotyping relied on rule-based algorithms …

Objective Accurate identification of self-harm presentations to Emergency Departments (ED)
can lead to more timely mental health support, aid in understanding the burden of suicidal …

Background Although suicide is a leading cause of death among children, the optimal
approach for using health care data sets to detect suicide-related emergencies among …